Split an untargeted metabolomics data set into a set of likely true
metabolites and a set of likely measurement artifacts. This process involves
comparing missing rates of pooled plasma samples and biological samples. The
functions assume a fixed injection order of samples where biological samples are
randomized and processed between intermittent pooled plasma samples. By comparing
patterns of missing data across injection order, metabolites that appear in blocks
and are likely artifacts can be separated from metabolites that seem to have
random dispersion of missing data. The two main metrics used are: 1. the number of
consecutive blocks of samples with present data and 2. the correlation of missing rates
between biological samples and flanking pooled plasma samples.